Surveillance programs are needed to guide mosquito-control operations to reduce both nuisance and the spread of mosquito-borne diseases. Understanding the thresholds for action to reduce both nuisance and the risk of arbovirus transmission is becoming critical. To date, mosquito surveillance is mainly implemented to inform about pathogen transmission risks rather than to reduce mosquito nuisance even though lots of control efforts are aimed at the latter. Passive surveillance, such as digital monitoring (validated by entomological trapping), is a powerful tool to record biting rates in real time. High-quality data are essential to model the risk of arbovirus diseases. For invasive pathogens, efforts are needed to predict the arrival of infected hosts linked to the small-scale vector to host contact ratio, while for endemic pathogens efforts are needed to set up region-wide highly structured surveillance measures to understand seasonal re-activation and pathogen transmission in order to carry out effective control operations.
Caputo, B.; Manica, M. (2020). Mosquito surveillance and disease outbreak risk models to inform mosquito-control operations in Europe. CURRENT OPINION IN INSECT SCIENCE, 39: 101-108. doi: 10.1016/j.cois.2020.03.009 handle: http://hdl.handle.net/10449/61208
Mosquito surveillance and disease outbreak risk models to inform mosquito-control operations in Europe
Manica, M.Ultimo
2020-01-01
Abstract
Surveillance programs are needed to guide mosquito-control operations to reduce both nuisance and the spread of mosquito-borne diseases. Understanding the thresholds for action to reduce both nuisance and the risk of arbovirus transmission is becoming critical. To date, mosquito surveillance is mainly implemented to inform about pathogen transmission risks rather than to reduce mosquito nuisance even though lots of control efforts are aimed at the latter. Passive surveillance, such as digital monitoring (validated by entomological trapping), is a powerful tool to record biting rates in real time. High-quality data are essential to model the risk of arbovirus diseases. For invasive pathogens, efforts are needed to predict the arrival of infected hosts linked to the small-scale vector to host contact ratio, while for endemic pathogens efforts are needed to set up region-wide highly structured surveillance measures to understand seasonal re-activation and pathogen transmission in order to carry out effective control operations.File | Dimensione | Formato | |
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